The rising cost of providing healthcare services has increased the consolidation of healthcare service providers and thus the size of integrated delivery networks (IDN). Management of large IDNs poses unique organizational problems. The result is often increased revenue cycles with respect to patient billing and poorer customer service. Existing task management structures are often not flexible enough to effectively handle the dynamic changes that occur on an on-going basis in large IDNs.
In order to manage the volume of data in IDNs, healthcare provider organizations have turned to sophisticated data management systems or applications. Typically, these systems include modules for maintaining or improving the quality of data. By improving the quality of data, i.e., correcting errors and or omissions in data, the revenue cycle for patient billing may be reduced and the overall service to customers may be improved. Generally, for each healthcare service provider in the IDN, a task list is developed and populated with tasks for improving data specific to that particular provider. A user such as a data clerk is often responsible for working the tasks that populate the task lists.
For large IDNs, the tasks that populate the task lists may include tasks input by users of the system, tasks input by third party systems, and tasks generated by the data management system itself. Prior art data management systems typically are not capable of integrating tasks from across an entire enterprise or IDN. Rather, prior art systems typically include a plurality of task lists and require users to “jump” from one task list to another to work tasks. In addition, prior art systems including multiple task lists do not allow a system administrator to easily manage all of the tasks in the system from a single interface. As a result, tasks are sometimes duplicated, lost, incorrectly entered, and incorrectly worked. Generally, system resources are often not efficiently used.